Mapping the Risk of Water Soil Erosion in Larrodrigo (Salamanca, Spain) Using the RUSLE Model and A-DInSAR Technique

The quantification of soil loss are studies driven by the importance of soil as a resource and are mainly due to risks of laminar and/or runoff water erosion. These problems directly affect the daily life of the population and serve as predictors of environmental effects. In this work, the quantific...

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Autores principales: Antonio Martínez-Graña, Jerymy Carrillo, Lorena Lombana, Marco Criado, Carlos Palacios
Formato: article
Lenguaje:EN
Publicado: MDPI AG 2021
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GIS
S
Acceso en línea:https://doaj.org/article/90c1466c79a94504a4db5162be5101fa
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Sumario:The quantification of soil loss are studies driven by the importance of soil as a resource and are mainly due to risks of laminar and/or runoff water erosion. These problems directly affect the daily life of the population and serve as predictors of environmental effects. In this work, the quantification and calculation of the sheet water erosion caused mainly by rainfall has been carried out in a study area located in the municipality of Larrodrigo (Salamanca, Spain), based on the simultaneous application of the RUSLE model with GIS techniques. Thematic cartographies have been generated to determine soil loss in Tm/Ha/year and mm/year based on the use of parameters of the physical environment (lithology, rainfall, slopes…) where the erosive risk is quantified and its applicability to the study area by spatio-temporal extrapolation techniques. Simultaneously, the use of the A-DInSAR technique was implemented to calculate average ground deformation velocities in mm/year associated with water erosion. Two sectors with greater vulnerability to water erosion have been detected within the area of interest: one of them called main, which corresponds to the slopes near the Larrodrigo stream, with soil losses showing values of 0.3- > 12 mm/year, and a secondary sector belonging to the tributaries or channels derived from the mainstream with values of 0.3- > 12 mm/year. This type of study makes it possible to manage and organise human support practicesin order to subsequently establish measures that can prevent, mitigate and/or correct those areas with the greatest damage.